An AI method combining retrieved information with generated responses.
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Retrieval-Augmented Generation (RAG) is an AI technique that improves the accuracy of AI-generated responses by combining a language model with an external information retrieval system. Instead of relying only on its trained knowledge, a RAG system first searches a database, website, document collection, or knowledge base to find relevant information and then uses that information to generate a more accurate and context-aware response. RAG helps reduce AI hallucinations, keeps responses more up to date, and allows AI systems to provide answers based on specific, trusted sources. In AI SEO and AEO, RAG increases the importance of creating well-structured, authoritative, and easily retrievable content that AI systems can find and cite.